scholarly journals Design of a novel multifunction decision support/alerting system for in-patient acute care, ICU and floor (AlertWatch AC)

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Douglas A. Colquhoun ◽  
Ryan P. Davis ◽  
Theodore T. Tremper ◽  
Jenny J. Mace ◽  
Jan M. Gombert ◽  
...  
Keyword(s):  
Decision Support ◽  
Operating Room ◽  
Acute Care ◽  
Care Team ◽  
Labor And Delivery ◽  
Process Of Care ◽  
Similar System ◽  
Hospital Units ◽  
High Acuity ◽  
High Level

Abstract Background Multifunction surveillance alerting systems have been found to be beneficial for the operating room and labor and delivery. This paper describes a similar system developed for in-hospital acute care environments, AlertWatch Acute Care (AWAC). Results A decision support surveillance system has been developed which extracts comprehensive electronic health record (EHR) data including live data from physiologic monitors and ventilators and incorporates them into an integrated organ icon-based patient display. Live data retrieved from the hospitals network are processed by presenting scrolling median values to reduce artifacts. A total of 48 possible alerts are generated covering a broad range of critical patient care concerns. Notification is achieved by paging or texting the appropriated member of the critical care team. Alerts range from simple out of range values to more complex programing of impending Ventilator Associated Events, SOFA, qSOFA, SIRS scores and process of care reminders for the management of glucose and sepsis. As with similar systems developed for the operating room and labor and delivery, there are green, yellow, and red configurable ranges for all parameters. A census view allows surveillance of an entire unit with flashing or text to voice alerting and enables detailed information by windowing into an individual patient view including live physiologic waveforms. The system runs via web interface on desktop as well as mobile devices, with iOS native app available, for ease of communication from any location. The goal is to improve safety and adherence to standard management protocols. Conclusions AWAC is designed to provide a high level surveillance view for multi-bed hospital units with varying acuity from standard floor patients to complex ICU care. Alerts are generated by algorithms running in the background and automatically notify the selected member of the patients care team. Its value has been demonstrated for low acuity patients, further study is required to determine its effectiveness in high acuity patients.

scholarly journals Barriers and facilitators to the adoption of electronic clinical decision support systems: a qualitative interview study with UK general practitioners

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Elizabeth Ford ◽  
Natalie Edelman ◽  
Laura Somers ◽  
Duncan Shrewsbury ◽  
Marcela Lopez Levy ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
General Practitioners ◽  
Clinical Decision Support ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Structured Interview ◽  
Qualitative Interview Study ◽  
High Level

Abstract Background Well-established electronic data capture in UK general practice means that algorithms, developed on patient data, can be used for automated clinical decision support systems (CDSSs). These can predict patient risk, help with prescribing safety, improve diagnosis and prompt clinicians to record extra data. However, there is persistent evidence of low uptake of CDSSs in the clinic. We interviewed UK General Practitioners (GPs) to understand what features of CDSSs, and the contexts of their use, facilitate or present barriers to their use. Methods We interviewed 11 practicing GPs in London and South England using a semi-structured interview schedule and discussed a hypothetical CDSS that could detect early signs of dementia. We applied thematic analysis to the anonymised interview transcripts. Results We identified three overarching themes: trust in individual CDSSs; usability of individual CDSSs; and usability of CDSSs in the broader practice context, to which nine subthemes contributed. Trust was affected by CDSS provenance, perceived threat to autonomy and clear management guidance. Usability was influenced by sensitivity to the patient context, CDSS flexibility, ease of control, and non-intrusiveness. CDSSs were more likely to be used by GPs if they did not contribute to alert proliferation and subsequent fatigue, or if GPs were provided with training in their use. Conclusions Building on these findings we make a number of recommendations for CDSS developers to consider when bringing a new CDSS into GP patient records systems. These include co-producing CDSS with GPs to improve fit within clinic workflow and wider practice systems, ensuring a high level of accuracy and a clear clinical pathway, and providing CDSS training for practice staff. These recommendations may reduce the proliferation of unhelpful alerts that can result in important decision-support being ignored.

scholarly journals Development of a Low-Resource Operating Room and a Wide-Awake Orthopedic Surgery Program During the COVID-19 Pandemic

2021 ◽  
pp. 155335062110035
Author(s):  
Justin J. Turcotte ◽  
Jeffrey M. Gelfand ◽  
Christopher M. Jones ◽  
Rubie S. Jackson
Keyword(s):  
Operating Room ◽  
Orthopedic Surgery ◽  
Physical Space ◽  
Surgical Care ◽  
Low Resource ◽  
High Acuity ◽  
Institutional Experience ◽  
Provider Shortages ◽  
Resource Replacement ◽  
Wide Awake

Introduction. The COVID-19 pandemic resulted in significant medication, supply and equipment, and provider shortages, limiting the resources available for provision of surgical care. In response to mandates restricting surgery to high-acuity procedures during this period, our institution developed a multidisciplinary Low-Resource Operating Room (LROR) Taskforce in April 2020. This study describes our institutional experience developing an LROR to maintain access to urgent surgical procedures during the peak of the COVID-19 pandemic. Methods. A delineation of available resources and resource replacement strategies was conducted, and a final institution-wide plan for operationalizing the LROR was formed. Specialty-specific subgroups then convened to determine best practices and opportunities for LROR utilization. Orthopedic surgery performed in the LROR using wide-awake local anesthesia no tourniquet (WALANT) is presented as a use case. Results. Overall, 19 limited resources were identified, spanning across the domains of physical space, drugs, devices and equipment, and personnel. Based on the assessment, the decision to proceed with creation of an LROR was made. Sixteen urgent orthopedic surgeries were successfully performed using WALANT without conversion to general anesthesia. Conclusion. In response to the COVID-19 pandemic, a LROR was successfully designed and operationalized. The process for development of a LROR and recommended strategies for operating in a resource-constrained environment may serve as a model for other institutions and facilitate rapid implementation of this care model should the need arise in future pandemic or disaster situations.

scholarly journals High Acuity Therapy Variation Across Pediatric Acute Care Cardiology Units: Results from the Pediatric Acute Care Cardiology Collaborative Hospital Surveys

2021 ◽  
Author(s):  
Ashraf S. Harahsheh ◽  
◽  
Alaina K. Kipps ◽  
Stephen A. Hart ◽  
Steven C. Cassidy ◽  
...  
Keyword(s):  
Acute Care ◽  
High Acuity

scholarly journals Modified early warning score-based clinical decision support: cost impact and clinical outcomes in sepsis

JAMIA Open ◽  
2020 ◽  
Vol 3 (2) ◽  
pp. 261-268
Author(s):  
Devin J Horton ◽  
Kencee K Graves ◽  
Polina V Kukhareva ◽  
Stacy A Johnson ◽  
Maribel Cedillo ◽  
...  
Keyword(s):  
Decision Support ◽  
Acute Care ◽  
Direct Cost ◽  
Clinical Decision Support ◽  
Early Warning ◽  
Clinical Decision ◽  
Early Warning Score ◽  
Total Direct Cost ◽  
Intervention Period ◽  
Support Cost

Abstract Objective The objective of this study was to assess the clinical and financial impact of a quality improvement project that utilized a modified Early Warning Score (mEWS)-based clinical decision support intervention targeting early recognition of sepsis decompensation. Materials and Methods We conducted a retrospective, interrupted time series study on all adult patients who received a diagnosis of sepsis and were exposed to an acute care floor with the intervention. Primary outcomes (total direct cost, length of stay [LOS], and mortality) were aggregated for each study month for the post-intervention period (March 1, 2016–February 28, 2017, n = 2118 visits) and compared to the pre-intervention period (November 1, 2014–October 31, 2015, n = 1546 visits). Results The intervention was associated with a decrease in median total direct cost and hospital LOS by 23% (P = .047) and .63 days (P = .059), respectively. There was no significant change in mortality. Discussion The implementation of an mEWS-based clinical decision support system in eight acute care floors at an academic medical center was associated with reduced total direct cost and LOS for patients hospitalized with sepsis. This was seen without an associated increase in intensive care unit utilization or broad-spectrum antibiotic use. Conclusion An automated sepsis decompensation detection system has the potential to improve clinical and financial outcomes such as LOS and total direct cost. Further evaluation is needed to validate generalizability and to understand the relative importance of individual elements of the intervention.

scholarly journals Impact of event notification services on timely follow-up and rehospitalization among primary care patients at two Veterans Affairs Medical Centers

2021 ◽  
Author(s):  
Brian E Dixon ◽  
Kimberly M Judon ◽  
Ashley L Schwartzkopf ◽  
Vivian M Guerrero ◽  
Nicholas S Koufacos ◽  
...  
Keyword(s):  
Primary Care ◽  
Usual Care ◽  
Acute Care ◽  
Health Systems ◽  
Veterans Affairs ◽  
Care Team ◽  
Primary Care Team ◽  
Medical Centers ◽  
Event Notification

Abstract Objective To examine the effectiveness of event notification service (ENS) alerts on health care delivery processes and outcomes for older adults. Materials and methods We deployed ENS alerts in 2 Veterans Affairs (VA) medical centers using regional health information exchange (HIE) networks from March 2016 to December 2019. Alerts targeted VA-based primary care teams when older patients (aged 65+ years) were hospitalized or attended emergency departments (ED) outside the VA system. We employed a concurrent cohort study to compare postdischarge outcomes between patients whose providers received ENS alerts and those that did not (usual care). Outcome measures included: timely follow-up postdischarge (actual phone call within 7 days or an in-person primary care visit within 30 days) and all-cause inpatient or ED readmission within 30 days. Generalized linear mixed models, accounting for clustering by primary care team, were used to compare outcomes between groups. Results Compared to usual care, veterans whose primary care team received notification of non-VA acute care encounters were 4 times more likely to have phone contact within 7 days (AOR = 4.10, P < .001) and 2 times more likely to have an in-person visit within 30 days (AOR = 1.98, P = .007). There were no significant differences between groups in hospital or ED utilization within 30 days of index discharge (P = .057). Discussion ENS was associated with increased timely follow-up following non-VA acute care events, but there was no associated change in 30-day readmission rates. Optimization of ENS processes may be required to scale use and impact across health systems. Conclusion Given the importance of ENS to the VA and other health systems, this study provides guidance for future research on ENS for improving care coordination and population outcomes. Trial Registration ClinicalTrials.gov NCT02689076. “Regional Data Exchange to Improve Care for Veterans After Non-VA Hospitalization.” Registered February 23, 2016.

scholarly journals Case-Based Reasoning with an Artificial Neural Network for Decision Support in Situations at Complex Technological Objects of Urban Infrastructure

2021 ◽  
Vol 4 (4) ◽  
pp. 73
Author(s):  
Igor Glukhikh ◽  
Dmitry Glukhikh
Keyword(s):  
Neural Network ◽  
Decision Support ◽  
Multilayer Perceptron ◽  
Network Architecture ◽  
Environmental Influence ◽  
Case Based Reasoning ◽  
Technological Object ◽  
Technological Facility ◽  
High Level ◽  
Case Based

The article considers the tasks of intellectual support for decision support in relation to a complex technological object. The relevance is determined by a high level of responsibility, together with a variety of possible situations at a complex technological facility. The authors consider case-based reasoning (CBR) as a method for decision support. For a complex technological object, the problem defined is the uniqueness of the situations, which is determined by a variety of elements and the possible environmental influence. This problem complicates the implementation of CBR, especially the stages of comparing situations and a further selection of the most similar situation from the database. As a solution to this problem, the authors consider the use of neural networks. The work examines two neural network architectures. The first part of the research presents a neural network model that builds upon the multilayer perceptron. The second part considers the “Comparator-Adder” architecture. Experiments have shown that the proposed neural network architecture “Comparator-Adder” showed higher accuracy than the multilayer perceptron for the considered tasks of comparing situations. The results have a high level of generalization and can be used for decision support in various subject areas and systems where complex technological objects arise.

Nurses' knowledge and attitude towards COVID-19 in the context of the acute health care settings in Jordan

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sajidah Alhwamdih ◽  
Hamzeh Y. Abunab ◽  
Abdullah Ahmad Algunmeeyn ◽  
Imad Alfayoumi ◽  
Sana Hawamdeh
Keyword(s):  
Health Care ◽  
Acute Care ◽  
Health Care Facilities ◽  
Content Type ◽  
Increased Risk ◽  
Level Of Knowledge ◽  
Acute Care Settings ◽  
Knowledge And Attitude ◽  
High Level ◽  
Nurses Knowledge

Purpose Nurses are at the front line in facing the COVID-19 outbreak and are at increased risk of becoming infected and might be the source of transmission in health-care facilities and the community. The purpose of this study is to assess the knowledge and attitude toward COVID1-19 among nurses in acute care settings in Jordan. This is expected to help with the global initiative to combat the COVID-19 epidemic. Design/methodology/approach A cross-sectional design was used to survey nurses' knowledge and attitude of COVID-19 among Jordanian nurses working in acute care settings. Findings The grand mean of knowledge items response was 8.94, implying that respondents possessed a high level of knowledge. The overall attitude score was positive for the participants, with a mean score of 5.93. Moreover, the results showed a significant relationship between knowledge and attitude scores. Originality/value The findings suggest that nurses in Jordan showed a high level of knowledge and a positive attitude toward COVID-19 during the outbreak's rapid rise period. This study showed specific aspects of knowledge and attitudes that should be focused on in future awareness and educational programs to promote all preventive and safety measures of COVID-19.

Data Warehousing for Decision Support

2011 ◽  
pp. 124-133
Author(s):  
John Wang ◽  
James Yao ◽  
Qiyang Chen
Keyword(s):  
Decision Support ◽  
Data Warehousing ◽  
Business Environment ◽  
External Information ◽  
Business Organizations ◽  
Negative Effects ◽  
Business Information ◽  
Business Opportunities ◽  
High Level ◽  
Business Complexity

Today’s business environment is dynamic and uncertain. Competition among business organizations is becoming more intensified and globalized. These business organizations’ demand for both internal and external information is growing rapidly. This rapidly growing demand to analyze business information has quickly led to the emergence of data warehousing (Finnegan, Murphy, & O’Riordan, 1999). The strategic use of information from data warehousing assures the solution of the negative effects of many of the challenges facing organizations (Love, 1996). When the data warehousing technologies are well positioned and properly implemented, they can assist organizations in reducing business complexity, discovering ways to leverage information for new sources of competitive advantage, realizing business opportunities, and providing a high level of information readiness to respond quickly and decisively under conditions of uncertainty (Love; Park, 1997).

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